The AI technology that could revolutionise asthma treatment
Asthma sufferers have become the subject of a new clinical study using AI to create personalised treatment plans for patients, reducing the guesswork in tackling respiratory illnesses.
It can seemingly come out of nowhere, suffocating the 2.8 million Australians who have it.
For some, treatment is as easy as using an inhaler. For others like Nicola Jansen, it's been a lifelong struggle.
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Asthma sufferers have become the subject of a new clinical study using AI to create personalised treatment plans for patients, reducing the guesswork in tackling respiratory illnesses. Nine
"Asthma is a really unpredictable type of respiratory issue," Jansen said.
"I've found myself in hospital, I've found myself on a nebuliser, having to take steroid-based medication.
"Everyone essentially is on generic plans, if you like, that are helpful and they're great, but they're not always effective."
But plans of attack, tailored to a patient's unique biological makeup, may soon be in our reach.
Melbourne-based biotech company Diag-Nose.io has been harnessing artificial intelligence to do just that.
They are training an algorithm by feeding it patient data so it can figure out how best to target not just asthma but a range of respiratory diseases.
"CT scans and X-rays and so forth look at how your lungs look," Diag-Nose.io chief executive Eldin Rostom said.
"Whereas for us, we look at the underlying biology."
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Asthma sufferers have become the subject of a new clinical study using AI to create personalised treatment plans for patients, reducing the guesswork in tackling respiratory illnesses. Nine
Specifically, they look at the biological relationship between a patient's nose and lungs.
A sample is collected using a nasal swab. It's then sent to a lab where a scientist extracts proteins.
That information is uploaded to an AI platform the company calls RhinoMap, which produces a report showing the likelihood a patient will respond to different medicines.
The company is working on a 48-hour turnaround for tests.
A clinical study of the technology is under way.
The method will eventually have to go through a rigorous approval process.
"We're hoping to get this in the hands of clinics and practitioners as early as late 2026," Rostom said.
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